The Big Mac Index 🍔 - Exploratory Data Analysis
Skills: R, Dplyr, Ggplot2, Plotly
Available in GitHub
Introduction
The Economist’s Big Mac Index was invented in 1986 as a lighthearted guide to whether currencies are at their “correct” level. It is based on the theory of purchasing-power parity (PPP), the notion that in the long run exchange rates should move towards the rate that would equalise the prices of an identical basket of goods and services (in this case, a burger) in any two countries.
Burgernomics was never intended as a precise gauge of currency misalignment, merely a tool to make exchange-rate theory more digestible. Yet the Big Mac index has become a global standard, included in several economic textbooks and the subject of dozens of academic studies.
In this project we will take a look at how the Big Mac index evolved in the last 20 years and draw some insights from the last edition, published in July 2021.
The Economist has made the data for the index (along with the scripts used for the calculations) available in their repository in GitHub. A list with the continent of each country that appears in the index will be added the allow further analysis.
| Name | df |
| Number of rows | 1520 |
| Number of columns | 20 |
| _______________________ | |
| Column type frequency: | |
| character | 4 |
| Date | 1 |
| numeric | 15 |
| ________________________ | |
| Group variables | None |
Variable type: character
| skim_variable | n_missing | complete_rate | min | max | empty | n_unique | whitespace |
|---|---|---|---|---|---|---|---|
| iso_a3 | 0 | 1 | 3 | 3 | 0 | 57 | 0 |
| currency_code | 0 | 1 | 3 | 3 | 0 | 58 | 0 |
| name | 0 | 1 | 3 | 20 | 0 | 58 | 0 |
| continent | 0 | 1 | 4 | 7 | 0 | 4 | 0 |
Variable type: Date
| skim_variable | n_missing | complete_rate | min | max | median | n_unique |
|---|---|---|---|---|---|---|
| date | 0 | 1 | 2000-04-01 | 2021-07-01 | 2014-01-01 | 35 |
Variable type: numeric
| skim_variable | n_missing | complete_rate | mean | sd | p0 | p25 | p50 | p75 | p100 | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| local_price | 0 | 1.00 | 29246.12 | 792628.45 | 1.05 | 7.62 | 26.91 | 130.00 | 30164100.00 | ▇▁▁▁▁ |
| dollar_ex | 0 | 1.00 | 5954.09 | 113824.12 | 0.30 | 3.07 | 7.76 | 51.08 | 3613989.07 | ▇▁▁▁▁ |
| dollar_price | 0 | 1.00 | 3.30 | 1.29 | 0.64 | 2.36 | 3.09 | 4.03 | 9.08 | ▃▇▃▁▁ |
| USD_raw | 0 | 1.00 | -0.24 | 0.30 | -0.87 | -0.45 | -0.30 | -0.08 | 1.27 | ▃▇▂▁▁ |
| EUR_raw | 0 | 1.00 | -0.23 | 0.28 | -0.83 | -0.44 | -0.28 | -0.07 | 0.87 | ▃▇▃▁▁ |
| GBP_raw | 0 | 1.00 | -0.18 | 0.30 | -0.85 | -0.40 | -0.23 | 0.00 | 1.14 | ▂▇▃▁▁ |
| JPY_raw | 0 | 1.00 | 0.04 | 0.39 | -0.79 | -0.25 | 0.00 | 0.23 | 2.16 | ▅▇▂▁▁ |
| CNY_raw | 0 | 1.00 | 0.46 | 0.63 | -0.76 | 0.03 | 0.30 | 0.79 | 4.39 | ▇▇▁▁▁ |
| GDP_dollar | 708 | 0.53 | 25536.98 | 22651.27 | 1049.75 | 7182.23 | 14812.56 | 41611.46 | 100578.97 | ▇▂▂▁▁ |
| adj_price | 708 | 0.53 | 3.72 | 0.96 | 2.33 | 2.98 | 3.34 | 4.42 | 7.43 | ▇▃▃▁▁ |
| USD_adjusted | 708 | 0.53 | -0.02 | 0.25 | -0.58 | -0.19 | -0.03 | 0.09 | 1.49 | ▃▇▁▁▁ |
| EUR_adjusted | 708 | 0.53 | -0.09 | 0.21 | -0.58 | -0.23 | -0.10 | 0.02 | 0.82 | ▂▇▅▁▁ |
| GBP_adjusted | 708 | 0.53 | 0.01 | 0.24 | -0.59 | -0.14 | 0.00 | 0.15 | 1.29 | ▂▇▂▁▁ |
| JPY_adjusted | 708 | 0.53 | 0.22 | 0.30 | -0.46 | 0.01 | 0.20 | 0.39 | 1.62 | ▂▇▃▁▁ |
| CNY_adjusted | 708 | 0.53 | 0.02 | 0.25 | -0.55 | -0.14 | 0.01 | 0.14 | 1.41 | ▂▇▂▁▁ |
The table above shows that the GDP and adjusted columns have missing values. This is because the adjusted index (based on the GDP per capita) was introduced in July 2011 and has a reduced number of countries, while the full index sometimes adds or removes countries.
The index is calculated over 5 ‘base’ currencies, but to keep it simple we will only analyze the one based on the US dollar (which is also the most representative), dropping the other ones. Country and currency codes will be also dropped.
Burgernomics across time
Since April 2000, there have been 35 editions of the index. While it was usually updated at the middle of each year (with some exceptions in 2006, 2007 and 2010), from 2012 it is updated in both January and July.
As it was previously said, The Economist sometimes adds or removes countries for the index. But how many haven’t always been part of the index? And which ones stayed on the least?
The countries that appeared the least are from the Middle East, Central America and Eastern Europe. They all were part of the index for 7 editions. Coincidence or not, they all have developing economies.
This leads us to another question: How is the trend? Does the overall number of countries included in the index change over time or there is always the same number that comes and goes?
We can see that there is a pattern to increase the number of countries in the index. In the last twenty years has gone from 28 to 57 countries, doubling its size.
Now, what has happened with the price of the Big Mac in the US, used as a base for all the other numbers to compare? As a reference, the American Consumer Price Index in the same period has increased a 59.4%.
Going from $2.51 to $5.65 the Big Mac has more than doubled its price in the US (a 125.1% increase to be precise), way more than the increase of the Consumer Price Index, which makes us question the reliability of the last one. Notice also that the price stayed stable in the years that followed financial crisis (the burst of the .com bubble in 2000, the subprime mortgages in 2008 and the COVID pandemic in 2020).
What happened with the price in the other countries? We made a ranking with the variations in their local currencies to get an idea.
The ranking shows us that the prices have increased in all the countries, altough in very different measures. While in countries like Israel, Switzerland and Taiwan they increased less than 20%, in Argentina the variation was of 15100%, which means that today you need 151 times the money you needed in 2000 to buy a Big Mac!
Having an idea about how the index evolved over time, we will next take a look at the last edition.
Burgernomics in 2021
First, we will rank the countries by the price in US dollars of the Big Mac, to see if there are any patterns.
There is a big difference between the top and the bottom of the ranking. A Big Mac in Switzerland costs up to 3.2 times more than in South Africa. We see that all the countries in the top of the list (except for Venezuela) are countries with a high GDP per capita, while the ones in the bottom have a low GDP.
To check if there is a correlation between the GDP per capita and the price of the Big Mac we are going to use a scatter plot.
Bonus track: currency volatility
While the main objective of the Big Mac Index is to determine wheter a country’s currency is too cheap or too expensive, the data can be used to draw alternative insights. For example, the volatility of a country’s exchange rate.
What is the relevance of this indicator? Let’s put it this way: Foreign investors inevitably seek out stable countries with strong economic performance in which to invest their capital. A country with such positive attributes will draw investment funds away from other countries perceived to have more political and economic risk.
By analyzing the standard deviation of each country’s adjusted index along time we can determine how stable are their exchange rates.